
RoboStruct Technologies builds intelligent robotics systems that improve accuracy, speed, and safety in manufacturing and logistics. It develops collaborative robots and AI-driven mechatronics platforms that integrate sensors, actuators, and control software to work with humans. The company operates in industrial automation and robotics engineering for businesses across sectors. Key technologies include AI, machine learning for perception and control, robotics hardware, and software integrations with factory systems. This approach supports scaling operations and making work safer and more efficient.

RoboStruct Technologies builds intelligent robotics systems that improve accuracy, speed, and safety in manufacturing and logistics. It develops collaborative robots and AI-driven mechatronics platforms that integrate sensors, actuators, and control software to work with humans. The company operates in industrial automation and robotics engineering for businesses across sectors. Key technologies include AI, machine learning for perception and control, robotics hardware, and software integrations with factory systems. This approach supports scaling operations and making work safer and more efficient.
Intern – Complex Systems Diagnostics & Prognostics Design (Summer 2026)
About the Role
We are looking for a highly motivated Summer Intern to join the Fleet Health Management & Remote Diagnostics team. In this role, you will contribute to a strategic initiative focused on building a unified Vehicle and Fleet Health Management (VHM/FHM) framework that enables predictive diagnostics and intelligent fault management across multiple vehicle platforms.
Working under the mentorship of senior engineers, you will help design scalable, AI-driven diagnostic and prognostic solutions that improve vehicle reliability, safety, and performance at both the individual vehicle and fleet levels.
Key Responsibilities
Contribute to Fleet Health Management (FHM) and Prognostics & Health Management (PHM) initiatives.
Support the development of a unified vehicle health monitoring framework applicable across vehicles, trims, and fleets.
Develop system health models for vehicle components, subsystems, and full systems using telemetry data, engineering inputs, and software diagnostics.
Build and maintain a scalable diagnostic knowledge base integrating vehicle architecture, hardware, and software.
Apply AI/ML techniques for early fault detection, root cause isolation, and failure mitigation.
Explore knowledge graphs and Large Language Models (LLMs) to enhance fault reasoning, automate diagnostic logic, and improve system explainability.
Collaborate closely with system architects and technical specialists to translate engineering knowledge into actionable diagnostic and prognostic models.
Required Qualifications
Strong foundation in AI/ML techniques for Prognostics & Health Management (PHM).
Solid understanding of systems engineering or vehicle architecture.
Experience with data analysis, time-series modeling, and anomaly detection.
Proficiency in Python or similar programming languages with ML libraries.
Familiarity with knowledge representation techniques, such as knowledge graphs.
Excellent written and verbal communication skills.
Ability to work both independently and collaboratively.
Currently enrolled in a Master’s or PhD program in Electrical Engineering, Mechanical Engineering, or a related field.
Proof of enrollment in a current or upcoming graduate program (MS or PhD).
Preferred Qualifications
Experience with vehicle telemetry systems or signal processing.
Familiarity with LLMs or generative AI frameworks.
Exposure to semantic modeling or ontology development.
Compensation
💰 $50.00 – $70.00 per hour
About Us
We are an internationally recognized HR consultancy leveraging AI-driven recruitment systems to connect top talent with leading companies, tech startups, and innovative projects worldwide. Our platform is free for candidates and designed to match skills with high-impact opportunities.
Note: Application submission is subject to profile evaluation by our Recruitment Specialists using our AI system. Further details will be shared upon resume submission.